Discovery of novel quinoline papain-like protease inhibitors for COVID-19 through topology constrained molecular generative model

Abstract

AbstractPapain-like protease (PLpro) plays a critical role in both viral polyprotein processing and host antiviral immune suppression in SARS-CoV-2 infection, which causes COVID-19. Although several drugs have been approved for COVID-19, such as Remdesivir, Nirmatrelvir etc., none of the PLproinhibitors have been approved for the treatment of COVID-19. The advent of artificial intelligence-based drug design methods has significantly accelerated the process of drug discovery. In current study, by harnessing the power of a topology constrained molecular generative model, we discovered a novel series of PLproinhibitors with strong potency against prevalent SARS-CoV-2 variants. Following a structure based computational approach for optimization, our lead compound, GZNL-2002, achieved decent PLproinhibitory potency and favorable pharmacokinetic properties, which warrants further development as a potential candidate compound for COVID-19 disease.